Diese Strategie nutzt dynamische mehrere EMAs als Einstiegssignale in Kombination mit Trailing Stop Loss und Gewinnzielmechanismen für das Risikomanagement. Sie nutzt die glättende Natur von EMAs, um Trends zu identifizieren und die Kosten über Multi-DCA-Einträge zu steuern. Darüber hinaus verbessert die Integration von adaptiven Stop Loss- und Gewinnnahmefunktionen den Automatisierungsprozess.
Die EMA-Strategie wird von den EMA-Perioden verwendet, in denen der Kurs innerhalb einer Reihe von EMA-Perioden überschreitet oder bewegt.
Sie beinhaltet mehrere Risikokontrollmechanismen:
Festlegung von Gewinnzielpreisen für Exits
/*backtest start: 2023-01-12 00:00:00 end: 2024-01-18 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=4 strategy("EMA DCA Strategy with Trailing Stop and Profit Target", overlay=true ) // Define the investment amount for when the condition is met investment_per_condition = 6 // Define the EMAs ema5 = ema(close, 5) ema10 = ema(close, 10) ema20 = ema(close, 20) ema50 = ema(close, 50) ema100 = ema(close, 100) ema200 = ema(close, 200) // Define ATR sell threshold atr_sell_threshold = input(title="ATR Sell Threshold", type=input.integer, defval=10, minval=1) // Helper function to find if the price is within 1% of the EMA isWithin1Percent(price, ema) => ema_min = ema * 0.99 ema_max = ema * 1.01 price >= ema_min and price <= ema_max // Control the number of buys var int buy_count = 0 buy_limit = input(title="Buy Limit", type=input.integer, defval=3000) // Calculate trailing stop and profit target levels trail_percent = input(title="Trailing Stop Percentage", type=input.integer, defval=1, minval=0, maxval=10) profit_target_percent = input(title="Profit Target Percentage", type=input.integer, defval=3, minval=1, maxval=10) // Determine if the conditions are met and execute the strategy checkConditionAndBuy(emaValue, emaName) => var int local_buy_count = 0 // Create a local mutable variable if isWithin1Percent(close, emaValue) and local_buy_count < buy_limit strategy.entry("Buy at " + emaName, strategy.long, qty=investment_per_condition / close, alert_message ="Buy condition met for " + emaName) local_buy_count := local_buy_count + 1 // alert("Buy Condition", "Buy condition met for ", freq_once_per_bar_close) local_buy_count // Return the updated local_buy_count // Add ATR sell condition atr_condition = atr(20) > atr_sell_threshold if atr_condition strategy.close_all() buy_count := 0 // Reset the global buy_count when selling // Strategy execution buy_count := checkConditionAndBuy(ema5, "EMA5") buy_count := checkConditionAndBuy(ema10, "EMA10") buy_count := checkConditionAndBuy(ema20, "EMA20") buy_count := checkConditionAndBuy(ema50, "EMA50") buy_count := checkConditionAndBuy(ema100, "EMA100") buy_count := checkConditionAndBuy(ema200, "EMA200") // Calculate trailing stop level trail_offset = close * trail_percent / 100 trail_level = close - trail_offset // Set profit target level profit_target_level = close * (1 + profit_target_percent / 100) // Exit strategy: Trailing Stop and Profit Target strategy.exit("TrailingStop", from_entry="Buy at EMA", trail_offset=trail_offset, trail_price=trail_level) strategy.exit("ProfitTarget", from_entry="Buy at EMA", when=close >= profit_target_level) // Plot EMAs plot(ema5, title="EMA 5", color=color.red) plot(ema10, title="EMA 10", color=color.orange) plot(ema20, title="EMA 20", color=color.yellow) plot(ema50, title="EMA 50", color=color.green) plot(ema100, title="EMA 100", color=color.blue) plot(ema200, title="EMA 200", color=color.purple)